Goldman Sachs is testing buyer interest as the data provider targets about $280M in 2026 recurring revenue, Reuters reports.
By RuntimeWire Staff · Published
Primary source: Reuters
Why it matters #
Vacanti and Moran turned the data exhaust from a daily-deals product into a recurring research platform. A $2.5B-plus sale would show how highly buyers value proprietary datasets as AI makes ordinary software easier to copy.
YipitData, founded by Vinicius Vacanti and James Moran, is exploring a sale that could value the New York data provider at $2.5 billion to $3 billion, Reuters reported on August 20th.
Goldman Sachs is advising YipitData, according to Reuters, which cited people familiar with early discussions involving strategic buyers and private equity firms. The process may not produce a transaction. The reported price range is an opening test of what buyers will pay for an information asset with proprietary datasets and recurring revenue, whose underlying data could become more valuable as artificial intelligence makes conventional software features easier to reproduce.
For Vacanti and Moran, a sale at that level would cap a long, unusually productive pivot. The founders left finance in 2007 to build internet products, and Vacanti eventually taught himself Python and Django after an outsourced prototype failed. Their original idea, Yipit, collected the daily deals flooding the market during Groupon's ascent. Vacanti has written that the founders built an early version in three days and initially entered and categorized deals by hand. The consumer product faded with the daily-deals market. The data machinery behind it survived.
The pivot became the asset
YipitData's founding dates reflect that transition. Reuters traces YipitData's history to 2010, when Yipit launched, while YipitData lists 2013 as the founding year of its current operation. Norwest Venture Partners' account supplies the connective tissue: Yipit began as a daily-deals aggregator in 2010, and the founders launched YipitData in 2013 after recognizing that their systems could turn web activity into research for institutional investors.
That pivot moved Vacanti and Moran from recommending discounted meals to selling evidence about how companies and markets were performing. YipitData now combines card transactions, receipts, web data and app-usage information with analyst research. YipitData says its coverage spans more than 500,000 companies and $1.8 trillion in business-to-business spending.
YipitData also says it serves more than 650 investors, brands and retailers and employs more than 750 people. Reuters named Walmart, Lowe's and Ulta Beauty among its customers. Those corporate accounts matter because they broaden YipitData beyond its original hedge-fund audience and give a prospective buyer a route into recurring enterprise research budgets.
The founders' finance backgrounds helped shape that product. Vacanti, a Harvard applied mathematics graduate, worked at Blackstone and Quadrangle before starting Yipit. Moran studied economics at Harvard and also worked at Blackstone. They understood the customer before they had the technology, then built the technical capability after Vacanti's experience with outsourcing forced the issue.
The reported price rests on sourced estimates
Reuters' sources said YipitData is targeting approximately $280 million in annual recurring revenue in 2026, with revenue growing by more than 30%. YipitData has not published those financial figures in the materials reviewed for this story, so the numbers remain estimates supplied by people familiar with the sale process.
A $2.5 billion to $3 billion valuation would equal roughly nine to 11 times the reported ARR target. That range would also put YipitData well above the valuation assigned during its last large financing. Carlyle led a Series E of up to $475 million in December 2021, taking YipitData's valuation above $1 billion. Norwest, which first invested in 2019, remained a shareholder.
The proposed range would therefore more than double YipitData's 2021 mark. It would not necessarily produce the same return for every shareholder because YipitData's ownership, debt and the mix of primary and secondary capital in earlier transactions are not detailed in the cited announcements.
A nearby private-market comparison shows why Carlyle is testing demand. AlphaSense said in June that it raised $350 million at a $7.5 billion valuation after exceeding $600 million in ARR, a multiple of about 12.5 times. AlphaSense sells a broader AI-driven market-intelligence platform and disclosed its own numbers, so the comparison is imperfect. It still shows that investors are assigning substantial prices to research platforms with proprietary content and recurring enterprise revenue.
AI changes the buyer's math
AI has weakened the defensibility of many software features. A competitor can reproduce interfaces and workflow tools faster than it can assemble years of licensed data, collection infrastructure, customer relationships and analyst expertise.
YipitData's appeal rests on that harder layer. Reuters reported that investor interest in proprietary datasets has risen partly because unique data can support AI models and partly because information assets can retain value as AI reduces spending on interchangeable software. The report did not identify any model trained on YipitData's datasets, and YipitData's public positioning remains focused on market intelligence for investors and corporations.
The stronger acquisition case is immediate: YipitData owns the infrastructure and operating knowledge needed to convert fragmented real-world activity into recurring research products. A strategic buyer could feed those products into a larger financial-data terminal, corporate intelligence suite or AI research workflow. A private equity buyer could pursue the same expansion while preserving YipitData as a standalone subscription provider.
Carlyle's 2021 investment was explicitly aimed at product development and expansion into new markets. Five years later, a sale process would test whether that expansion created an asset worth as much as $3 billion. The outcome will depend on whether bidders price YipitData as a research provider growing above 30%, an alternative-data supplier with durable collection advantages, or an AI-era information asset that would take years to rebuild.
Vacanti and Moran began with a short-lived consumer trend and kept the valuable machinery. The potential sale is the clearest market test yet of what that machinery is worth.